Abstract
In this paper we describe STAHLp, a system that constructs componential models of chemical substances. STAHLp is a descendant of Zytkow and Simon's (1986) STAHL system, and both use chemical reactions and known componential models in order to construct new chemical models. However, STAHLp employs a more unified and effective strategy for recovering from erroneous inferences, based partly on de Kleer's (1984) assumption-based method of belief revision. This involves recording the underlying source beliefs or premises which lead to each inferred reaction or model. Where Zytkow and Simon's system required multiple methods for detecting errors and recovering from them, STAHLp uses a more powerful representation and additional rules which allow a unified method for error detection and recovery. When given the same initial data, the new system constructs the same historically correct models as STAHL, but it has other capabilities as well. In particular, STAHLp can modify data it has been given if this is necessary to achieve consistent models, and then proceed to construct new models based on the revised data.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
References
Black, J. (1756). Experiments upon magnesia alba, quicklime, and some other alkaline substances. In Essays and observations, physical and literary.Edinburgh
de Kleer, J. (1984). Choices without backtracking. In Proceedings of the Fourth National Conference on Artificial Intelligence(pp.79–85). Austin, Tx: Morgan-Kaufmann.
Doyle, J. (1979). A truth maintenance system.Artificial Intelligence, 12, 231–272.
Gay-Lussac, L.P., & Thenard, L.J. (1808). Sur les metaux de la potasse et de la soude.Annales de chimie, 66, 205–217.
Gay-Lussac, L.P., & Thenard, L.J. (1810). Observations.Annales de chimie, 75, 290–316.
Jones, R. (1986). Generating predictions to aid the scientific discovery process. In Proceedings of the Fifth National Conference on Artificial Intelligence (pp.513–517). Philadelphia: Morgan-Kaufmann.
Langley, P., Ohlsson, S., Thibadeau, R., & Walter, R. (1984). Cognitive architectures and principles of behavior. In Proceedings of the Sixth Conference of the Cognitive Science Society (pp.244–247). Boulder, Co.
Langley, P., Simon, H.A., Bradshaw, G. L., and Zytkow, J. M. (1986).Scientific discovery:A com-putational account of the creative processes. Cambridge, MA: MIT Press.
Stillman, J.M. (1960).The story of alchemy and early chemistry. New York: Dover Publications.
Zytkow, J.M., & Simon, H.A. (1986). A theory of historical discovery:The construction of com-ponential models. Machine Learning, 1, 107–136.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Rose, D., Langley, P. Chemical Discovery as Belief Revision. Machine Learning 1, 423–452 (1986). https://doi.org/10.1023/A:1022870800276
Issue Date:
DOI: https://doi.org/10.1023/A:1022870800276